Unit Commitment problem (UC) is a large family of mathematical optimization problems usually either match the energy demand at minimum cost or maximize revenues from energy production. This paper proposes a new approach for solving Unit Commitment problem using the EADPSODV technique. In PSODV, the appropriate mutation factor is selected by applying Ant Colony search procedure in which internally a Genetic Algorithm (GA) is employed in order to develop the necessary Ant Colony parameters. In EADPSODV method the advantageous part is that, for determining the most feasible configuration of the control variables in the Unit Commitment. An initial observation and verification of the suggested process is carried on a 10-unit system which is extended to 40-unit system over a stipulated time horizon (24hr). The outcomes attained from the proposed EADPSODV approach indicate that EADPSODV provides effective and robust solution of Unit Commitment.
A Modified ANT Colony Algorithm for Solving the Unit Commitment Problem
